Literature DB >> 30947553

Nerve Conduction Studies in Surgical Cubital Tunnel Syndrome Patients.

Daniel J Shubert1, Joseph Prud'homme1, Shafic Sraj1.   

Abstract

Background: Electrodiagnostic studies (EDX) serve a prominent role in the diagnostic workup of cubital tunnel syndrome (CBTS), but their reported sensitivity varies widely. The goals of our study were to determine the sensitivity of EDX in a cohort of patients who responded well to surgical cubital tunnel release (CBTR), and whether the implementation of the Association of Neuromuscular and Electrodiagnostic Medicine (AANEM) criteria improves the sensitivity.
Methods: We identified 118 elbows with clinical CBTS who had preoperative EDX and underwent CBTR. The EDX diagnoses were CBTS, ulnar neuropathy (UN), and normal ulnar nerves. We divided the 118 elbows into those that received above-elbow stimulation (XE group) and those that did not (non-XE group). We calculated the sensitivities for all groups and reinterpreted the results according to the AANEM guidelines.
Results: Cubital tunnel release provided significant relief in 93.6% of the elbows. Based on the EDX reports, 11% patients had clear CBTS, 23% had UN, and 66% showed no UN. The sensitivities were 11.7% for CBTS and 34.2% for any UN. In the XE group, the sensitivity of the EDX reports for CBTS and UN climbed to 33.3% and 58.3%, respectively. When we calculated the across-elbow motor nerve conduction velocity, the sensitivity for CBTS and UN was 87.5% and 100%, respectively. The XE and non-XE groups showed no difference except for sex, bilaterality, concomitant carpal tunnel release, and obesity (P < .05).
Conclusion: Implementing AANEM guidelines results in significant improvement in correlation of clinical and electrodiagnostic findings of CBTS.

Entities:  

Keywords:  cubital tunnel syndrome; electrodiagnostic; nerve conduction study; sensitivity

Mesh:

Year:  2019        PMID: 30947553      PMCID: PMC8041427          DOI: 10.1177/1558944719840750

Source DB:  PubMed          Journal:  Hand (N Y)        ISSN: 1558-9447


  21 in total

Review 1.  Sonography in the diagnosis of carpal tunnel syndrome: a critical review of the literature.

Authors:  Roy Beekman; Leo H Visser
Journal:  Muscle Nerve       Date:  2003-01       Impact factor: 3.217

2.  Which motor nerve conduction study is best in ulnar neuropathy at the elbow?

Authors:  Ali Shakir; Paula J Micklesen; Lawrence R Robinson
Journal:  Muscle Nerve       Date:  2004-04       Impact factor: 3.217

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Authors:  M A Posner
Journal:  J Am Acad Orthop Surg       Date:  1998 Sep-Oct       Impact factor: 3.020

Review 4.  Clinical features and electrodiagnosis of ulnar neuropathies.

Authors:  Mark E Landau; William W Campbell
Journal:  Phys Med Rehabil Clin N Am       Date:  2012-10-25       Impact factor: 1.784

5.  Comparison of the flexed and extended elbow positions in localizing ulnar neuropathy at the elbow.

Authors:  M J Kothari; D C Preston
Journal:  Muscle Nerve       Date:  1995-03       Impact factor: 3.217

Review 6.  Ulnar neuropathy: evaluation and management.

Authors:  Christopher J Dy; Susan E Mackinnon
Journal:  Curr Rev Musculoskelet Med       Date:  2016-06

7.  The Prevalence of Cubital Tunnel Syndrome: A Cross-Sectional Study in a U.S. Metropolitan Cohort.

Authors:  Tonya W An; Bradley A Evanoff; Martin I Boyer; Daniel A Osei
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Review 8.  Compressive neuropathies of the upper extremity: update on pathophysiology, classification, and electrodiagnostic findings.

Authors:  Minal Tapadia; Tahseen Mozaffar; Ranjan Gupta
Journal:  J Hand Surg Am       Date:  2010-03-11       Impact factor: 2.230

9.  Anatomical relationships and branching patterns of the dorsal cutaneous branch of the ulnar nerve.

Authors:  Cassie G Root; Daniel A London; Nicole S Schroeder; Ryan P Calfee
Journal:  J Hand Surg Am       Date:  2013-06       Impact factor: 2.230

10.  Muscle atrophy at diagnosis of carpal and cubital tunnel syndrome.

Authors:  Paige Mallette; Meijuan Zhao; David Zurakowski; David Ring
Journal:  J Hand Surg Am       Date:  2007 Jul-Aug       Impact factor: 2.230

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  1 in total

1.  Diagnosis of Cubital Tunnel Syndrome Using Deep Learning on Ultrasonographic Images.

Authors:  Issei Shinohara; Atsuyuki Inui; Yutaka Mifune; Hanako Nishimoto; Kohei Yamaura; Shintaro Mukohara; Tomoya Yoshikawa; Tatsuo Kato; Takahiro Furukawa; Yuichi Hoshino; Takehiko Matsushita; Ryosuke Kuroda
Journal:  Diagnostics (Basel)       Date:  2022-03-04
  1 in total

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